Hydrocarbon Processing - October 2022 - 62

Digital Technologies
Identified periods of interest can be
viewed as capsules used for near-realtime
monitoring and diagnostics of industrial
processes, enabling SMEs to
identify problem sources quickly, thereby
accelerating troubleshooting efforts. As
learning takes place, these ML applications
are highly scalable because a model
built on a single asset can be used to initialize
monitoring of other similar assets.
FIG. 1. A no-code ML proprietary applicationa incorporates a workflow that can be used
by SMEs to create models and identify periods of interest, regardless of the SMEs' backgrounds
in ML or statistics.
Real-world results. By empowering
process experts to capitalize on their
strengths, increased value can be driven
at an industry level, as demonstrated by
the following two case studies.
Building operational technology
(OT) friendly asset monitoring models
in the North Sea. In the oil and gas
industry, maintaining and maximizing
the lifetime of critical assets-including
pumps, valves, heat exchangers and
compressors-are vital to profitable operation.
Although this example is for upstream
operations, similar principles apply
for downstream plants and facilities,
as they use much of the same equipment.
The failure of oil export pumps can
FIG. 2. An oil and gas operator used a proprietary ML applicationa to automatically identify and
mitigate abnormal operating conditions, thus reducing failure rates of oil export pumps.
lead to a facility-wide shutdown, and repairs
of this highly specialized equipment
can be costly and lengthy in duration.
Without a proactive condition-based
maintenance program in place, plant
personnel run the risk of unplanned
shutdowns, reduced production, and environmental
and safety issues-leaving
facilities vulnerable.
To monitor its pumps of this type,
Ithaca Energy, an oil and gas operator,
implemented a proprietary ML applicationa
the
cleansed process instrumentation
tags identified as relevant by a process
expert. Next, the company leaned on historic
examples of unplanned downtime
events and normal operation within the
application to establish baseline and abnormal
conditions for the ML application
to use in this analysis.
After letting the model run through
FIG. 3. The proprietary ML applicationa identified a factor increasing the likelihood of failure
in an allnex product development campaign. By adjusting this parameter, the team saw
significant savings.
62 OCTOBER 2022 | HydrocarbonProcessing.com
several iterations, users reviewed results
of the application's condition detection.
It was determined that the model correctly
identified precursors and signal
contributors for past downtime events,
so Ithaca commissioned the application
to run in near real time, utilizing current
operational data to assess the risk of future
failure. Built-in online diagnostics
were instructive for understanding key
contributors to pump failures, and for
directing further investigative and troubleshooting
efforts (FIG. 2).
, building an ML model and using
http://www.HydrocarbonProcessing.com

Hydrocarbon Processing - October 2022

Table of Contents for the Digital Edition of Hydrocarbon Processing - October 2022

Contents
Hydrocarbon Processing - October 2022 - Cover1
Hydrocarbon Processing - October 2022 - Cover2
Hydrocarbon Processing - October 2022 - Contents
Hydrocarbon Processing - October 2022 - 4
Hydrocarbon Processing - October 2022 - 5
Hydrocarbon Processing - October 2022 - 6
Hydrocarbon Processing - October 2022 - 7
Hydrocarbon Processing - October 2022 - 8
Hydrocarbon Processing - October 2022 - 9
Hydrocarbon Processing - October 2022 - 10
Hydrocarbon Processing - October 2022 - 10A
Hydrocarbon Processing - October 2022 - 10B
Hydrocarbon Processing - October 2022 - 10C
Hydrocarbon Processing - October 2022 - 10D
Hydrocarbon Processing - October 2022 - 11
Hydrocarbon Processing - October 2022 - 12
Hydrocarbon Processing - October 2022 - 13
Hydrocarbon Processing - October 2022 - 14
Hydrocarbon Processing - October 2022 - 15
Hydrocarbon Processing - October 2022 - 16
Hydrocarbon Processing - October 2022 - 17
Hydrocarbon Processing - October 2022 - 18
Hydrocarbon Processing - October 2022 - 19
Hydrocarbon Processing - October 2022 - 20
Hydrocarbon Processing - October 2022 - 21
Hydrocarbon Processing - October 2022 - 22
Hydrocarbon Processing - October 2022 - 23
Hydrocarbon Processing - October 2022 - 24
Hydrocarbon Processing - October 2022 - 25
Hydrocarbon Processing - October 2022 - 26
Hydrocarbon Processing - October 2022 - 27
Hydrocarbon Processing - October 2022 - 28
Hydrocarbon Processing - October 2022 - 29
Hydrocarbon Processing - October 2022 - 30
Hydrocarbon Processing - October 2022 - 31
Hydrocarbon Processing - October 2022 - 32
Hydrocarbon Processing - October 2022 - 33
Hydrocarbon Processing - October 2022 - 34
Hydrocarbon Processing - October 2022 - 35
Hydrocarbon Processing - October 2022 - 36
Hydrocarbon Processing - October 2022 - 37
Hydrocarbon Processing - October 2022 - 38
Hydrocarbon Processing - October 2022 - 39
Hydrocarbon Processing - October 2022 - 40
Hydrocarbon Processing - October 2022 - 41
Hydrocarbon Processing - October 2022 - 42
Hydrocarbon Processing - October 2022 - 43
Hydrocarbon Processing - October 2022 - 44
Hydrocarbon Processing - October 2022 - 45
Hydrocarbon Processing - October 2022 - 46
Hydrocarbon Processing - October 2022 - 47
Hydrocarbon Processing - October 2022 - 48
Hydrocarbon Processing - October 2022 - 49
Hydrocarbon Processing - October 2022 - 50
Hydrocarbon Processing - October 2022 - 51
Hydrocarbon Processing - October 2022 - 52
Hydrocarbon Processing - October 2022 - 53
Hydrocarbon Processing - October 2022 - 54
Hydrocarbon Processing - October 2022 - 55
Hydrocarbon Processing - October 2022 - 56
Hydrocarbon Processing - October 2022 - 56A
Hydrocarbon Processing - October 2022 - 56B
Hydrocarbon Processing - October 2022 - 56C
Hydrocarbon Processing - October 2022 - 56D
Hydrocarbon Processing - October 2022 - 56E
Hydrocarbon Processing - October 2022 - 56F
Hydrocarbon Processing - October 2022 - 56G
Hydrocarbon Processing - October 2022 - 56H
Hydrocarbon Processing - October 2022 - 57
Hydrocarbon Processing - October 2022 - 58
Hydrocarbon Processing - October 2022 - 59
Hydrocarbon Processing - October 2022 - 60
Hydrocarbon Processing - October 2022 - 60A
Hydrocarbon Processing - October 2022 - 60B
Hydrocarbon Processing - October 2022 - 60C
Hydrocarbon Processing - October 2022 - 60D
Hydrocarbon Processing - October 2022 - 60E
Hydrocarbon Processing - October 2022 - 60F
Hydrocarbon Processing - October 2022 - 61
Hydrocarbon Processing - October 2022 - 62
Hydrocarbon Processing - October 2022 - 63
Hydrocarbon Processing - October 2022 - 64
Hydrocarbon Processing - October 2022 - 64A
Hydrocarbon Processing - October 2022 - 64B
Hydrocarbon Processing - October 2022 - 65
Hydrocarbon Processing - October 2022 - 66
Hydrocarbon Processing - October 2022 - Cover3
Hydrocarbon Processing - October 2022 - Cover4
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https://www.nxtbook.com/nxtbooks/gulfpub/petrochemical_2018_v2
https://www.nxtbook.com/nxtbooks/gulfpub/petrochemical_2018
https://www.nxtbook.com/nxtbooks/gulfpub/hp_201812
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